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Secondary radar signal processing method based on deep four-channel network

A secondary radar and signal processing technology, applied in the radar field, can solve problems such as analog signal distortion, data transmission rate impact, and harmful transmission, and achieve the effects of reducing feature loss, excellent denoising performance, and reducing learning rate

Active Publication Date: 2020-09-01
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Claims
  • Application Information

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Problems solved by technology

The signal received by ground equipment from space cannot contain only useful signals. During the transmission process, there will be various noises mixed with useful signals. The coexistence of noise and signals in the channel is harmful to transmission. Its existence The analog signal is distorted, the digital signal is errored, and the data transmission rate is also affected

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  • Secondary radar signal processing method based on deep four-channel network
  • Secondary radar signal processing method based on deep four-channel network

Examples

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Embodiment

[0021] This example includes the following steps:

[0022] Step 1: Dataset preparation.

[0023] The secondary radar response signal with a total number of samples of 40000 and a time step of 512 is taken as sample data. Add the demodulated response signal of Gaussian white noise with signal-to-noise ratio SNR=5 as training data, denoted as X={x ij |i=1,2,...,N; j=1,2,...,K}, where N=40000, K=512. The response signal without adding noise is used as the training label, denoted as Y={y ij |i=1,2,...,N; j=1,2,...,K}. And divide it into training set, verification set and test set with the ratio of (0.8,0.1,0.1).

[0024] Step 2: Preprocessing the dataset.

[0025] Randomly scramble the training sample data of the secondary radar response signal, expand the dimension of the sample data X and label Y, and form a 3D tensor in the form of (n, t, f), where n represents the number of samples, and t=512 represents Time step, f represents the number of feature layers. and normalize...

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Abstract

The invention belongs to the technical field of radars, and particularly relates to a secondary radar signal denoising processing method based on a deep four-channel network. According to the specificscheme, firstly, a secondary radar response signal data set is prepared, and data set division and data set preprocessing are carried out; and then a novel deep four-channel neural network is constructed based on deep learning, wherein the novel deep four-channel neural network is formed by connecting four neural branches in parallel; the four paths can fully fuse learned different deep signal features, so that feature loss is reduced; and finally, the secondary radar test data are input into the deep four-channel neural network to suppress noise, and timing response signals are predicted. The method has very high denoising performance, and meets the requirement of noise suppression when the secondary radar receives the response signal.

Description

technical field [0001] The invention belongs to the technical field of radar, in particular to a secondary radar signal processing method based on a deep four-channel network. Background technique [0002] Secondary radar is a radio electronic positioning and identification system composed of interrogating radar and responding radar. The interrogating radar emits electromagnetic waves, the responding radar is triggered after receiving the interrogating electromagnetic waves, and emits responding electromagnetic waves, and the interrogating radar works according to the received responding electromagnetic waves to realize identification and position measurement. The interrogation radar of the secondary radar and the response radar on the target work together according to active scanning interrogation and passive response. The interrogation radar is generally fixed on the ground, the pulse of its scanning beam is coded with the interrogation signal, and the response pulse of t...

Claims

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Application Information

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IPC IPC(8): G01S13/78G01S13/76G01S7/41G01S7/292
CPCG01S13/78G01S13/76G01S7/292G01S7/418G01S7/417Y02A90/10
Inventor 沈晓峰都雪廖阔潘光松
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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